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, 15 (7), 810-8

Future Challenges for Clinical Care of an Ageing Population Infected With HIV: A Modelling Study

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Future Challenges for Clinical Care of an Ageing Population Infected With HIV: A Modelling Study

Mikaela Smit et al. Lancet Infect Dis.

Erratum in

  • Corrections.
    Lancet Infect Dis. 2015 Sep;15(9):998. doi: 10.1016/S1473-3099(15)00230-3. Epub 2015 Jul 26. Lancet Infect Dis. 2015. PMID: 26333319 Free PMC article. No abstract available.

Abstract

Background: The population infected with HIV is getting older and these people will increasingly develop age-related non-communicable diseases (NCDs). We aimed to quantify the scale of the change and the implications for HIV care in the Netherlands in the future.

Methods: We constructed an individual-based model of the ageing HIV-infected population, which followed patients on HIV treatment as they age, develop NCDs-including cardiovascular disease (hypertension, hypercholesterolaemia, myocardial infarctions, and strokes), diabetes, chronic kidney disease, osteoporosis, and non-AIDS malignancies-and start co-medication for these diseases. The model was parameterised by use of data for 10 278 patients from the national Dutch ATHENA cohort between 1996 and 2010. We made projections up to 2030.

Findings: Our model suggests that the median age of HIV-infected patients on combination antiretroviral therapy (ART) will increase from 43·9 years in 2010 to 56·6 in 2030, with the proportion of HIV-infected patients aged 50 years or older increasing from 28% in 2010 to 73% in 2030. In 2030, we predict that 84% of HIV-infected patients will have at least one NCD, up from 29% in 2010, with 28% of HIV-infected patients in 2030 having three or more NCDs. 54% of HIV-infected patients will be prescribed co-medications in 2030, compared with 13% in 2010, with 20% taking three or more co-medications. Most of this change will be driven by increasing prevalence of cardiovascular disease and associated drugs. Because of contraindications and drug-drug interactions, in 2030, 40% of patients could have complications with the currently recommended first-line HIV regimens.

Interpretation: The profile of patients in the Netherlands infected with HIV is changing, with increasing numbers of older patients with multiple morbidities. These changes mean that, in the near future, HIV care will increasingly need to draw on a wide range of medical disciplines, in addition to evidence-based screening and monitoring protocols to ensure continued high-quality care. These findings are based on a large dataset of HIV-infected patients in the Netherlands, but we believe that the overall patterns will be repeated elsewhere in Europe and North America. The implications of such a trend for care of HIV-infected patients in high-burden countries in Africa could present a particular challenge.

Funding: Medical Research Council, Bill & Melinda Gates Foundation, Rush Foundation, and Netherlands Ministry of Health, Welfare and Sport.

Figures

Figure 1
Figure 1
Schematic of the model of an ageing HIV-infected population The model follows HIV-infected patients from the start of treatment until death or last year of model (2030). The model simulates how, over time, HIV-infected patients age, develop comorbidities, start co-medication for these conditions, and how these co-medications affect HIV treatment. The dashed square shows the comorbidities and interactions included in the model. Patients developed comorbidities as a function of age and sex. Comedication is prescribed on the basis of the comorbidities a patient has, which in turn affect drug–drug interactions with HIV treatment (ART). Mortality risk is affected by both age and the number and type of comorbidity and is simulated for patients on ART. ART=antiretroviral therapy.
Figure 2
Figure 2
Projected age distribution of HIV-infected patients The red box shows the age distribution of patients on antiretroviral therapy in clinical care in the Netherlands in 2010, which matches the data exactly, and the blue box shows model output from 2011–30.
Figure 3
Figure 3
Predicted comorbitities (A) Predicted burden of NCDs in HIV-infected patients between 2010 and 2030 as simulated by the model. (B) Distribution of the number of NCDs by age group for HIV-infected and HIV-uninfected patients in 2030. NCD=non-communicable disease.
Figure 4
Figure 4
Predicted co-medications (A) Predicted burden of co-medications in HIV-infected patients between 2010 and 2030. (B) Predicted prevalence of comedication in 2030 as cross-section of number of patients on the different types of co-medications, based on a representative 400 patients (each square represents a patient). NCD=non-communicable disease.

Comment in

  • Predictions of geriatric HIV in 2030.
    Vance DE, Cody SL. Vance DE, et al. Lancet Infect Dis. 2015 Jul;15(7):753-4. doi: 10.1016/S1473-3099(15)00063-8. Epub 2015 Jun 9. Lancet Infect Dis. 2015. PMID: 26070968 No abstract available.
  • Respiratory co-morbidities in people with HIV.
    Brown J, Smith C, Johnson M, Lipman M, Abubakar I. Brown J, et al. Lancet Infect Dis. 2016 Jan;16(1):21. doi: 10.1016/S1473-3099(15)00468-5. Lancet Infect Dis. 2016. PMID: 26738830 No abstract available.

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